Tag Archives: long-term problems

Biodiversity Science

Protecting biodiversity is a goal of most people who value the environment. My question is what are the goals of biodiversity science and how do we achieve them? Some history is in order here. The term ‘biodiversity’ was coined in the 1980s as the complete biosphere including all species and ecosystems on Earth. The idea of cataloguing all the species on Earth was present many decades before this time, since the origin of the biological sciences. By the 1990s ‘biodiversity conservation’ became a popular subject and has grown greatly since then as a companion to CO2 emissions and the climate change problem. The twin broad goals of biodiversity science and biodiversity conservation are (1) to name and describe all the species on Earth, and (2), to protect all species from extinction, preventing a loss of biodiversity. How can we achieve these two goals?

The first goal of describing species faces challenges from disagreements over what a species is or is not. The old description of a species was to describe what group it was part of, and then how different this particular species was from other members of the group. In the good old days this was primarily based on reproductive incompatibility between species, if no successful reproduction, must be a new species. This simple common-sense view was subject to many attacks since some organisms that we see as different can in fact interbreed. Lions and tigers breed together and are an example, but if their interbred offspring are sterile, clearly, they are two different species. But many arguments arose because there was no data available for 99% of species to know if they could interbreed or not. The fallback position has been to describe the anatomy of a potential species and its relatives and judge from anatomy how different they were. Endless arguments followed, egged on by naturalists who pointed out that if the elephants in India were separated by a continent from elephants in Africa, clearly, they must be different species defined by geography. Many academic wars were fought over these issues.

Then in 1953 the structure of DNA was unravelled, and a new era dawned because with advances in technology of decoding genes we could describe species in a completely new way by determining how much DNA they had in common. But what is the magic percentage of common DNA? Humans and chimpanzees have 98.6% of their DNA in common, but despite this high similarity no one argues that they are the same species.

Despite this uncertainty the answer now seems much simpler: sequence the DNA of everything and you will have the true tree of life for defining separate species. While this was a dream 20 years ago, it is now a technical reality with rapid sequencing methods to help us get criminals and define species. Problem (1) solved?

Enter the lonely ecologist into this fray. Ecologists do not just want names, they wish to understand the function of each of the ‘species’ within communities and ecosystems, how does all this biodiversity interact to produce what we see in the landscape? For the moment we have approximately 10 million species on Earth, but somewhere around 80% of these ‘species’ are still undescribed. So now we have a clash of biodiversity visions, we cannot describe all the species on Earth even on the time scale of centuries, so we cannot achieve goal (1) of biodiversity science in any reasonable time. We have measured the DNA sequence of thousands of organisms that we can capture but we cannot describe them formally as species in the older sense. Perhaps it is akin to having all the phone numbers in the New York City phone book but not knowing to whom the numbers belong.

But the more immediate problem comes with objective (2) to prevent extinctions. Enter the conservation ecologist. The first problem is discussed above, we ecologists have no way of knowing how many species are in danger of extinction. We must look for rare or declining species, but we have complete inventory for few places on Earth. We must concentrate on large mammals and birds, and hope that they act as umbrella species and represent all of biodiversity. When we do have information on threatened species, for the most part there is no money to do the ecological studies needed to reverse declines in abundance. If there is money to list species and give a recovery plan on paper, then we find there is no money to implement the recovery plan. The Species-At-Risk act in Canada was passed in 2002 and has generated many recovery plans mostly for vertebrate species that have come to their attention. Almost none of these recovery plans have been completed, so in general we are all in favour of preventing extinctions but only it if costs us nothing. By and large the politics of preventing extinctions is very strongly supported, but the economic value of extinctions is nearly zero.

None of this is very cheery to conservation biologists. Two approaches have been suggested. The first is Big Science, use satellites and drones to scan the Earth every year to describe changes in landscapes and from these images infer biodiversity ‘health’. Simple and very expensive with AI to the rescue. But while we can see largescale landscape changes, the crux is to do something about them, and it is here that we fail because of the wall of climate change that we have no control over at present. Big Science may well assist us in seeing patterns of change, but it produces no path to understanding food webs or mediating changes in threatened populations. The second is small-scale biodiversity studies that focus on what species are present, how their numbers are changing, and what are the causes of change. Difficult, possible, but very expensive because you must put biologists in the field, on the ground to do the relevant measurements over a long-time frame. The techniques are there to use, thanks to much work on ecological methods in the past. What is missing again is the money. There are a few good examples of this small-scale approach but without good organization and good funding many of these attempts stop after too few years of data.

We are left with a dilemma of a particular science, Biodiversity Science, that has no way of achieving either of its two main objectives to name and to protect species on a global level. On a local level we can adopt partial methods of success by designating and protecting national parks and marine protected areas, and by studying only a few important species, the keystone species of food webs. But then we need extensive research to determine how to protect these areas and species from the inexorable march of climate change, which has singlehandedly complicated achieving biodiversity science’s two goals. Alas at the present time we may have another science to join the description of economics as a “dismal science” And we have not even started to discuss bacteria, viruses, and fungi.

Coffey, B. & Wescott, G. (2010) New directions in biodiversity policy and governance? A critique of Victoria’s Land and Biodiversity White Paper. Australasian Journal of Environmental Management 17: 204-214. doi: 10.1080/14486563.2010.9725268.

Donfrancesco, V., Allen, B.L., Appleby, R., et al. (2023) Understanding conflict among experts working on controversial species: A case study on the Australian dingo. Conservation Science and Practice 5: e12900. doi: 10.1111/csp2.12900.

Ritchie, J., Skerrett, M. & Glasgow, A. (2023) Young people’s climate leadership in Aotearoa. Journal of Peace Education, 12-2023: 1-23. doi: 10.1080/17400201.2023.2289649.

Sengupta, A., Bhan, M., Bhatia, S., Joshi, A., Kuriakose, S. & Seshadri, K.S. (2024) Realizing “30 × 30” in India: The potential, the challenges, and the way forward. Conservation Letters 2024, e13004. doi: 10.1111/conl.13004.

Wang, Q., Li, X.C. & Zhou, X.H. (2023) New shortcut for conservation: The combination management strategy of “keystone species” plus “umbrella species” based on food web structure. Biological Conservation 286: 110265.doi. 10.1016/j.biocon.2023.110265.

Do We Need to Replicate Ecological Experiments?

If you read papers on the philosophy of science you will very quickly come across the concept of replication, the requirement to test the same hypothesis twice or more before you become too attached to your conclusions. As a new student or a research scientist you face this problem when you wish to replicate some previous study. If you do replicate, you risk being classed as an inferior scientist with no ideas of your own. If you refuse to replicate and try something new, you will be criticized as reckless and not building a solid foundation in your science.  

There is an excellent literature discussing the problem of replication in ecology in particular and science in general. Nichols et al. (2019) argue persuasively that a single experiment is not enough. Amrheim et al. (2019) approach the problem from a statistical point of view and caution that single statistical tests are a shaky platform for drawing solid conclusions. They point out that statistical tests not only test hypotheses, but also countless assumptions and particularly for ecological studies the exact plant and animal community in which the study takes place. In contrast to ecological science, medicine probably has more replication problems at the other extreme – too many replications – leading to a waste of research money and talent. (Siontis and Ioannidis 2018).

A graduate seminar could profitably focus on a list of the most critical experiments or generalizations of our time in any subdiscipline of ecology. Given such a list we could ask if the conclusions still stand as time has passed, or perhaps if climate change has upset the older predictions, or whether the observations or experiments have been replicated to test the strength of conclusions. We can develop a stronger science of ecology only if we recognize both the strengths and the limitations of our current ideas.

Baker (2016) approached this issue by asking the simple question “Is there a reproducibility crisis?” Her results are well worth visiting. She had to cast a wide net in the sciences so unfortunately there are no details specific to ecological science in this paper. A similar question in ecology would have to distinguish observational studies and experimental manipulations to narrow down a current view of this issue. An interesting example is explored in Parker (2013) who analyzed a particular hypothesis in evolutionary biology about plumage colour in a single bird species, and the array of problems of an extensive literature on sexual selection in this field is astonishing.

A critic might argue that ecology is largely a descriptive science that should not expect to develop observational or experimental conclusions that will extend very much beyond the present. If that is the case, one might argue that replication over time is important for deciding when an established principle is no longer valid. Ecological predictions based on current knowledge may have much less reliability than we would hope, but the only way to find out is to replicate. Scientific progress depends on identifying goals and determining how far we have progressed to achieving these goals (Currie 2019). To advance we need to discuss replication in ecology.

Amrhein, V., Trafinnow, D. & Greenland, S. (2019) Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. American Statistician, 73, 262-270. doi: 10.1080/00031305.2018.1543137.

Baker, M. (2016) Is there a reproducibility crisis in science? Nature, 533, 452-454.

Currie, D.J. (2019) Where Newton might have taken ecology. Global Ecology and Biogeography, 28, 18-27. doi: 10.1111/geb.12842.

Nichols, J.D., Kendall, W.L. & Boomer, G.S. (2019) Accumulating evidence in ecology: Once is not enough. Ecology and Evolution, 9, 13991-14004. doi: 10.1002/ece3.5836.

Parker, T.H. (2013) What do we really know about the signalling role of plumage colour in blue tits? A case study of impediments to progress in evolutionary biology. Biological Reviews, 88, 511-536. doi: 10.1111/brv.12013.

Siontis, K.C. & Ioannidis, J.P.A. (2018) Replication, duplication, and waste in a quarter million systematic reviews and meta-analyses. Circulation: Cardiovascular quality and outcomes, 11, e005212. doi: 10.1161/CIRCOUTCOMES.118.005212.

On Ecology and Medicine

As I grow older and interact more with doctors, it occurred to me that the two sciences of medicine and ecology have very much in common. That is probably not a very new idea, but it may be worth spending time on looking at the similarities and differences of these two areas of science that impinge on our lives. The key question for both is how do we sort out problems? Ecologists worry about population, community and ecosystem problems that have two distinguishing features. First, the problems are complex and the major finding of this generation of ecologists is to begin to understand and appreciate how complex they are. Second, the major problems that need solving to improve conservation and wildlife management are difficult to study with the classical tools of experimental, manipulative scientific methods. We do what we can to achieve scientific paradigms but there are many loose ends we can only wave our hands about. As an example, take any community or ecosystem under threat of global warming. If we heat up the oceans, many corals will die along with the many animals that depend on them. But not all corals will die, nor will all the fish and invertebrate species, and the ecologists is asked to predict what will happen to this ecosystem under global warming. We may well understand from rigorous laboratory research about temperature tolerances of corals, but to apply this to the real world of corals in oceans undergoing many chemical and physical changes we can only make some approximate guesses. We can argue adaptation, but we do not know the limits or the many possible directions of what we predict will happen.

Now consider the poor physician who must deal with only one species, Homo sapiens, and the many interacting organs in the body, the large number of possible diseases that can affect our well-being, the stresses and strains that we ourselves cause, and the physician must make a judgement of what to do to solve your particular problem. If you have a broken arm, it is simple thankfully. If you have severe headaches or dizziness, many different causes come into play. There is no need to go into details that we all appreciate, but the key point is that physicians must solve problems of health with judgements but typically with no ability to do the kinds of experimental work we can do with mice or rabbits in the laboratory. And the result is that the physician’s judgements may be wrong in some cases, leading possibly to lawyers arguing for damages, and one appreciates that once we leave the world of medical science and enter the world of lawyers, all hope for solutions is near impossible.

There is now some hope that artificial intelligence will solve many of these problems both in ecological science and in medicine, but this belief is based on the premise that we know everything, and the only problem is to find the solutions in some forgotten textbook or scientific paper that has escaped our memory as humans. To ask that artificial intelligence will solve these basic problems is problematic because AI depends on past knowledge and science solves problems by future research.

Everyone is in favour of personal good health, but alas not everyone favours good environmental science because money is involved. We live in a world where major problems with climate change have had solutions presented for more than 50 years, but little more than words are presented as the solutions rather than action. This highlights one of the main differences between medicine and ecology. Medical issues are immediate since we have active lives and a limited time span of life. Ecological issues are long-term and rarely present an immediate short-term solution. Setting aside protected areas is in the best cases a long-term solution to conservation issues, but money for field research is never long term and ecologists do not live forever. Success stories for endangered species often require 10-20 years or more before success can be achieved; research grants are typically presented as 3- or 5-year proposals. The time scale we face as ecologists is like that of climate scientists. In a world of immediate daily concerns in medicine as in ecology, long-term problems are easily lost to view.

There has been an explosion of papers in the last few years on artificial intelligence as a potentially key process to use for answering both ecological and medical questions (e.g. Buchelt et al. 2024, Christin, Hervet, and Lecomte, 2019, Desjardins-Proulx, Poisot, & Gravel, 2019). It remains to be seen exactly how AI will help us to answer complex questions in ecology and medicine. AI is very good in looking back, but will it be useful to solve our current and future problems? Perhaps we still need to continue training good experimental scientists in ecology and in medicine.  

Buchelt, A., Buchelt, A., Adrowitzer, A. & Holzinger, A. (2024) Exploring artificial intelligence for applications of drones in forest ecology and management. Forest Ecology and Management, 551, 121530. doi: 10.1016/j.foreco.2023.121530.

Christin, S., Hervet, É. & Lecomte, N. (2019) Applications for deep learning in ecology. Methods in Ecology and Evolution, 10, 1632-1644. doi: 10.1111/2041-210X.13256.

Desjardins-Proulx, P., Poisot, T. & Gravel, D. (2019) Artificial Intelligence for ecological and evolutionary synthesis. Frontiers in Ecology and Evolution, 7. doi: 10.3389/fevo.2019.00402.

The Problem of Time in Ecology

There is a problem in doing ecological studies that is too little discussed – what is the time frame of a good study? The normal response would be that the time frame varies with each study so that no guidelines can be provided. There is increasing recognition that more long-term studies are needed in ecology (e.g. Hughes et al. 2017) but the guidelines remain unclear.

The first issue is usually to specify a time frame, e.g. 5 years, 10 years. But this puts the cart before the horse, as the first step ought to be to define the hypothesis being investigated. In practice hypotheses in many ecological papers are poorly presented and there should not be one hypothesis but a series of alternative hypotheses. Given that, the question of time can be given with more insight. How many replicated time periods do you need to measure the ecological variables in the study? If your time scale unit is one year, 2 or 3 years is not enough to come to any except very tentative conclusions. We have instantly fallen into a central dilemma of ecology – studies are typically planned and financed on a 3–5-year time scale, the scale of university degrees.

Now we come up against the fact of climate change and the dilemma of trying to understand a changing system when almost all field work assumes an unchanging environment. Taken to some extreme we might argue that what happens in this decade tells us little about what will happen in the next decade. The way around this problem is to design experiments to test the variables that are changing ahead of time, e.g., what a 5⁰C temperature increase will do to the survival of your corals. To follow this approach, which is the classic experimental approach of science, we must assume we know the major variables affecting our population or community changes. At present we do not know the answer to this question, and we rely on correlations of a few variables as predictors of how large a change to expect.

There is no way out of this empirical box, which defines clearly how physics and chemistry differ from ecology and medicine. There are already many large-scale illustrations of this problem. Forest companies cut down old-growth timber on the assumption that they can get the forest back by replanting seedlings in the harvested area. But what species of tree seedlings should we replant if we are concerned that reforestation often operates on a 100–500-year time scale? And in most cases, there is no consideration of the total disruption of the ecosystem, and we ignore all the non-harvestable biodiversity. Much research is now available on reforestation and the ecological problems it produces. Hole-nesting birds can be threatened if old trees with holes are removed for forestry or agricultural clearing (Saunders et al. 2023). Replanting trees after fire in British Columbia did not increase carbon storage over 55 years of recovery when compared with unplanted sites (Clason et al. 2022). Consequently, in some forest ecosystems tree planting may not be useful if carbon storage is the desired goal.

At the least we should have more long-term monitoring of the survival of replanted forest tree seedlings so that the economics of planting could be evaluated. Short-term Australian studies in replanted agricultural fields showed over 4 years differences in survival of different plant species (Jellinek et al. 2020). For an on-the-ground point of view story about tree planting in British Columbia see:
https://thetyee.ca/Opinion/2023/11/02/Dont-Thank-Me-Being-Tree-Planter/. But we need longer-term studies on control and replanted sites to be more certain of effective restoration management. Gibson et al. (2022) highlighted the fact that citizen science over a 20-year study could make a major contribution to measuring the effectiveness of replanting. Money is always in short supply in field ecology and citizen science is one way of achieving goals without too much cost. 

Forest restoration is only one example of applied ecology in which long-term studies are too infrequent. The scale of restoration of temperate and boreal ecosystems is around 100 years, and this points to one of the main failures of long-term studies, that they are difficult to carry on after the retirement of the principal investigators who designed the studies.

The Park Grass Experiment begun in 1856 on 2.8 ha of grassland in England is the oldest ecological experiment in existence (Silvertown et al. 2006). As such it is worth a careful evaluation for the questions it asked and did not ask, for the scale of the experiment, and for the experimental design. It raises the question of generality for all long-term studies and cautions us about the utility and viability of many of the large-scale, long-term studies now in progress or planned for the future.

The message of this discussion is that we should plan for long-term studies for most of our critical ecological problems with clear hypotheses of how to conserve biodiversity and manage our agricultural landscapes and forests. We should move away from 2–3-year thesis projects on isolated issues and concentrate on team efforts that address critical long-term issues with specific hypotheses. Which says in a nutshell that we must develop a vision that goes beyond our past practices in scatter-shot, short-term ecology and at the same time avoid poorly designed long-term studies of the future.

Clason, A.J., Farnell, I. & Lilles, E.B. (2022) Carbon 5–60 Years After Fire: Planting Trees Does Not Compensate for Losses in Dead Wood Stores. Frontiers in Forests and Global Change, 5, 868024. doi: 10.3389/ffgc.2022.868024.

Gibson, M., Maron, M., Taws, N., Simmonds, J.S. & Walsh, J.C. (2022) Use of citizen science datasets to test effects of grazing exclusion and replanting on Australian woodland birds. Restoration Ecology, 30, e13610. doi: 10.1111/rec.13610.

Hughes, B.B.,et al. (2017) Long-term studies contribute disproportionately to ecology and policy. BioScience, 67, 271-281. doi.: 10.1093/biosci/biw185.

Jellinek, S., Harrison, P.A., Tuck, J. & Te, T. (2020) Replanting agricultural landscapes: how well do plants survive after habitat restoration? Restoration Ecology, 28, 1454-1463. doi: 10.1111/rec.13242.

Saunders, D.A., Dawson, R. & Mawson, P.R. (2023) Artificial nesting hollows for the conservation of Carnaby’s cockatoo Calyptorhynchus latirostris: definitely not a case of erect and forget. Pacific Conservation Biology, 29, 119-129. doi: 10.1071/PC21061.

Silvertown, J., Silvertown, J., Poulton, P. & Biss, P.M. (2006) The Park Grass Experiment 1856–2006: its contribution to ecology. Journal of Ecology, 94, 801-814. doi: 10.1111/j.1365-2745.2006.01145.x.

The Ecological Outlook

There is an extensive literature on ecological traps going back two decades (e.g. Schlaepfer et al. 2002, Kristan 2003, Battin 2004) discussing the consequences of particular species selecting a habitat for breeding that is now unsuitable. A good example is discussed in Lamb et al. (2017) for grizzly bears in southeastern British Columbia in areas of high human contact. The ecological trap hypothesis has for the most part been discussed in relation to species threatened by human developments with some examples of whole ecosystems and human disturbances (e.g. Lindenmayer and Taylor 2020). The concept of an ecological trap can be applied to the Whole Earth Ecosystem, as has been detailed in the IPCC 2022 reports and it is this global ecological trap that I wish to discuss.

The key question for ecologists concerned about global biodiversity is how much biodiversity will be left after the next century of human disturbances. The ecological outlook is grim as you can hear every day on the media. The global community of ecologists can ameliorate biodiversity loss but cannot stop it except on a very local scale. The ecological problem operates on a century time scale, just the same as the political and social change required to escape the global ecological trap. E.O. Wilson (2016) wrote passionately about our need to set aside half of the Earth for biodiversity. Alas, this was not to be. Dinerstein et al. (2019) reduced the target to 30% in the “30 by 30” initiative, subsequently endorsed by 100 countries by 2022. Although a noble political target, there is no scientific evidence that 30 by 30 will protect the world’s biodiversity. Saunders et al. (2023) determined that for North America only a small percentage of refugia (5– 14% in Mexico, 4–10% in Canada, and 2–6% in the USA) are currently protected under four possible warming scenarios ranging from +1.5⁰C to +4⁰C. And beyond +2⁰C refugia will be valuable only if they are at high latitudes and high elevations.

The problem as many people have stated is that we are marching into an ecological trap of the greatest dimension. A combination of global climate change and continually increasing human populations and impacts are the main driving factors, neither of which are under the control of the ecological community. What ecologists and conservationists can do is work on the social-political front to protect more areas and keep analysing the dynamics of declining species in local areas. We confront major political and social obstacles in conservation ecology, but we can increase our efforts to describe how organisms interact in natural ecosystems and how we can reduce undesirable declines in populations. All this requires much more monitoring of how ecosystems are changing on a local level and depends on how successful we can be as scientists to diagnose and solve the ecological components of ecosystem collapse.

As with all serious problems we advance by looking clearly into what we can do in the future based on what we have learned in the past. And we must recognize that these problems are multi-generational and will not be solved in any one person’s lifetime. So, as we continue to march into the ultimate ecological trap, we must rally to recognize the trap and use strong policies to reverse its adverse effects on biodiversity and ultimately to humans themselves. None of us can opt out of this challenge.

There is much need in this dilemma for good science, for good ecology, and for good education on what will reverse the continuing degradation of our planet Earth. Every bit counts. Every Greta Thunberg counts.

Battin, J. (2004) When good animals love bad habitats: ecological traps and the conservation of animal populations. Conservation Biology, 18, 1482-1491.

Dinerstein, E., Vynne, C., Sala, E., et al. (2019) A Global Deal For Nature: Guiding principles, milestones, and targets. Science Advances, 5, eaaw2869.doi: 10.1126/sciadv.aaw2869..

IPCC, 2022b. In: Skea, J., Shukla, P.R., et al. (Eds.), Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of theIntergovernmental Panel on Climate Change. Cambridge University Press. doi: www.ipcc.ch/report/ar6/wg3/.

Kristan III, W.B. (2003) The role of habitat selection behavior in population dynamics: source–sink systems and ecological traps. Oikos, 103, 457-468.

Lamb, C.T., Mowat, G., McLellan, B.N., Nielsen, S.E. & Boutin, S. (2017) Forbidden fruit: human settlement and abundant fruit create an ecological trap for an apex omnivore. Journal of Animal Ecology, 86, 55-65. doi. 10.1111/1365-2656.12589.

Lindenmayer, D.B. and Taylor, C. (2020) New spatial analyses of Australian wildfires highlight the need for new fire, resource, and conservation policies. Proceedings of the National Academy of Sciences 117, 12481-124485. doi. 10.1073/pnas.2002269117.

Saunders, S.P., Grand, J., Bateman, B.L., Meek, M., Wilsey, C.B., Forstenhaeusler, N., Graham, E., Warren, R. & Price, J. (2023) Integrating climate-change refugia into 30 by 30 conservation planning in North America. Frontiers in Ecology and the Environment, 21, 77-84. doi. 10.1002/fee.2592.

Schlaepfer, M.A., Runge, M.C. & Sherman, P.W. (2002) Ecological and evolutionary traps. Trends in Ecology & Evolution, 17, 474-480.

Wilson, E.O. (2016) Half-Earth: Our Planet’s Fight for Life. Liveright, New York. ISBN: 978-1-63149-252-5.

The Meaningless of Random Sampling

Statisticians tell us that random sampling is necessary for making general inferences from the particular to the general. If field ecologists accept this dictum, we can only conclude that it is very difficult to nearly impossible to reach generality. We can reach conclusions about specific local areas, and that is valuable, but much of our current ecological wisdom on populations and communities relies on the faulty model of non-random sampling. We rarely try to define the statistical ‘population’ which we are studying and attempting to make inferences about with our data. Some examples might be useful to illustrate this problem.

Marine ecologists ae mostly agreed that sea surface temperature rise is destroying coral reef ecosystems. This is certainly true, but it camouflages the fact that very few square kilometres of coral reefs like the Great Barrier Reef have been comprehensively studied with a proper sampling design (e.g. Green 1979, Lewis 2004). When we analyse the details of coral reef declines, we find that many species are affected by rising sea temperatures, but some are not, and it is possible that some species will adapt by natural selection to the higher temperatures. So we quite rightly raise the alarm about the future of coral reefs. But in doing so we neglect in many cases to specify the statistical ‘population’ to which our conclusions apply.

Most people would agree that such an approach to generalizing ecological findings is tantamount to saying the problem is “how many angels can dance on the head of a pin”, and in practice we can ignore the problem and generalize from the studied reefs to all reefs. And scientists would point out that physics and chemistry seek generality and ignore this problem because one can do chemistry in Zurich or in Toronto and use the same laws that do not change with time or place. But the ecosystems of today are not going to be the ecosystems of tomorrow, so generality in time cannot be guaranteed, as paleoecologists have long ago pointed out.

It is the spatial problem of field studies that collides most strongly with the statistical rule to random sample. Consider a hypothetical example of a large national park that has recently been burned by this year’s fires in the Northern Hemisphere. If we wish to measure the recovery process of the vegetation, we need to set out plots to resample. We have two choices: (1) lay out as many plots as possible, and sample these for several years to plot recovery. Or (2) lay out plots at random each year, never repeating the same exact areas to satisfy the specifications of statisticians to “random sample” the recovery in the park. We typically would do (1) for two reasons. Setting up new plots each year as per (2) would greatly increase the initial field work of defining the random plots and would probably mean that travel time between the plots would be greatly increased. Using approach (1) we would probably set out plots with relatively easy access from roads or trails to minimize costs of sampling. We ignore the advice of statisticians because of our real-world constraints of time and money. And we hope to answer the initial questions about recovery with this simpler design.

I could find few papers in the ecological literature that discuss this general problem of inference from the particular to the general (Ives 2018, Hauss 2018) and only one that deals with a real-world situation (Ducatez 2019). I would be glad to be sent more references on this problem by readers.

The bottom line is that if your supervisor or research coordinator criticizes your field work because your study areas are not randomly placed or your replicate sites were not chosen at random, tell him or her politely that virtually no ecological research in the field is done by truly random sampling. Does this make our research less useful for achieving ecological understanding – probably not. And we might note that medical science works in exactly the same way field ecologists work, do what you can with the money and time you have. The law that scientific knowledge requires random sampling is often a pseudo-problem in my opinion.  

Ducatez, S. (2019) Which sharks attract research? Analyses of the distribution of research effort in sharks reveal significant non-random knowledge biases. Reviews in Fish Biology and Fisheries, 29, 355-367. doi. 10.1007/s11160-019-09556-0

Green, R.H. (1979) Sampling Design and Statistical Methods for Environmental Biologists. Wiley, New York. 257 pp.

Hauss, K. (2018) Statistical Inference from Non-Random Samples. Problems in Application and Possible Solutions in Evaluation Research. Zeitschrift fur Evaluation, 17, 219-240. doi.

Ives, A.R. (2018) Informative Irreproducibility and the Use of Experiments in Ecology. BioScience, 68, 746-747. doi. 10.1093/biosci/biy090

Lewis, J. (2004) Has random sampling been neglected in coral reef faunal surveys? Coral Reefs, 23, 192-194. doi: 10.1007/s00338-004-0377-y.

The Time Frame of Ecological Science

Ecological research differs from many branches of science in having a more convoluted time frame. Most of the sciences proceed along paths that are more often than not linear – results A → results B → results C and so on. Of course, these are never straight linear sequences and were described eloquently by Platt (1964) as strong inference:

“Strong inference consists of applying the following steps to every problem in science, formally and explicitly and regularly: 1) Devising alternative hypotheses; 2) Devising a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly as possible, exclude one or more of the hypotheses; 3) Carrying out the experiment so as to get a clean result; “Recycling the procedure, making sequential hypotheses to refine the possibilities that remain; and so on. It is like climbing a tree.” (page 347 in Platt).

If there is one paper that I would recommend all ecologists read it is this paper which is old but really is timeless and critical in our scientific research. It should be a required discussion topic for every graduate student in ecology.

Some ecological science progresses as Platt (1964) suggests and makes good progress, but much of ecology is lost in a failure to specify alternative hypotheses, in changing questions, in abandoning topics because they are too difficult, and in a shortage of time. It is the time component of ecological research that I wish to discuss in this blog.

The idea of long-term studies has always been present in ecology but was perhaps brought to our focus by the compilation by Gene Likens in 1989 in a book of 14 chapters that are as vital now as they were 34 years ago. Many discussions of long-term studies are now available to examine this issue. Buma et al. (2019) for example discuss plant primary succession at Glacier Bay, Alaska which has 100 years of data, and which illustrates in a very slow ecosystem a test of conventional rules of community development. Cusser et al. (2021) follow this by asking a critical question of how long field experiments need to be. They restrict long-term to be > 10 years of study and used data from the USA LTER sites. This question depends very much on the community or ecosystem of study. Studies in areas with a stable climate produced results more quickly than those in highly seasonal environments, and plant studies needed to be longer term than animal studies to reach stable conclusions. Ten years may not be enough.

Reinke et al. (2019) reviewed 3 long term field studies and suggest that long-term studies can be useful to allow us to predict how ecosystems will change with time. All these studies lead to three unanswered questions that are critical for progress in ecology. The first question is how we decide as a community exactly which ecological system we should be studying long-term. No one knows how to answer this question, and a useful graduate seminar could debate the utility of what are now considered model long-term studies, such as the three highlighted in Reinke et al. (2019) or the Park Grass Experiment (Addy et al. 2022). At the moment these decisions are opportunistic, and we should debate how best to proceed. Clearly, we cannot do everything for every population and community of interest, so how do we choose? We need model systems that can be applied to a wide variety of environments across the globe and that ask questions of global significance. Many groups of ecologists are trying to do this, but a host of decisions about who to fund and support in what institution are vital to avoid long-term studies driven more by convenience than by ecological importance.

A second question involves the implied disagreement whether many important questions in ecology today could be answered by short-term studies, so we reach a position where there is competition between short- and long-term funding. These decisions about where to do what for how long are largely uncontrolled. One would prefer to see an articulated set of hypotheses and predictions to proceed with decision making, whether for short-term studies suitable for graduate students or particularly for long-term studies that exceed the life of individual researchers.

A third question is the most difficult one of the objectives of long-term research. Given climate change as it is moving today, the hope that long-term studies will give us reliable predictions of changes in communities and ecosystems is at risk, the same problem of extrapolating a regression line beyond the range of the data. Depending on the answer to this climate dilemma, we could drop back to the suggestion that because we have only a poor ability to predict ecological change, we should concentrate more on widespread monitoring programs and less on highly localized studies of a few sites that are of unknown generality. Testing models with long-term data is enriching the ecological literature (e.g. Addy et al 2022). But the challenge is whether our current understanding is sufficient to make predictions for future populations or communities. Should ecology adopt the paradigm of global weather stations?

Addy, J.W.G., Ellis, R.H., MacLaren, C., Macdonald, A.J., Semenov, M.A. & Mead, A. (2022) A heteroskedastic model of Park Grass spring hay yields in response to weather suggests continuing yield decline with climate change in future decades. Journal of the Royal Society Interface, 19, 20220361. doi: 10.1098/rsif.2022.0361.

Buma, B., Bisbing, S.M., Wiles, G. & Bidlack, A.L. (2019) 100 yr of primary succession highlights stochasticity and competition driving community establishment and stability. Ecology, 100, e02885. doi: 10.1002/ecy.2885.

Cusser, S., Helms IV, J., Bahlai, C.A. & Haddad, N.M. (2021) How long do population level field experiments need to be? Utilising data from the 40-year-old LTER network. Ecology Letters, 24, 1103-1111. doi: 10.1111/ele.13710.

Hughes, B.B., Beas-Luna, R., Barner, A., et al. (2017) Long-term studies contribute disproportionately to ecology and policy. BioScience, 67, 271-281. doi: 10.1093/biosci/biw185.

Likens, G.E. (Editor, 1989) Long-term Studies in Ecology: Approaches and Alternatives. Springer Verlag, New York. 214 pp. ISBN: 0387967435.

Platt, J.R. (1964) Strong inference. Science, 146, 347-353. doi: 10.1126/science.146.3642.347.

Reinke, B.A., Miller, D.A.W. & Janzen, F.J. (2019) What have long-term field studies taught as about population dynamics? Annual Review of Ecology, Evolution, and Systematics, 50, 261-278. doi: 10.1146/annurev-ecolsys-110218-024717.

The Five Stages of Conservation

While listening to the reports on the COP 15 meeting in Montreal I began thinking that one way to look at conservation science and action is to think of it in 5 stages. So I decided to put out this discussion of how we might view all the conservation news.

Stage 1: Recognize the Issue

The most important issue is to make both scientists and the general public aware that there is a large problem with the conservation of the Earth’s biota. We start with having to convince all that biodiversity does not mean dangerous animals and plants. This stage would be simple for anyone who has taken a good biology course in school, but we still find that some people fear the “environment” because it is synonymous with spiders and alligators and bears and wolves. One might think that children’s books involving cute or anthropomorphised animals would make them less susceptible to this worry, but this does not work for all who have read “The Big Bad Wolf” and Little Red Riding Hood. So education about animals and plants should begin to point everyone toward conservation.

Stage 2: Become Concerned

People see that animals die from a great array of problems, and this connects to the human world where people get ill and pass away or become injured in a car accident. Depending on what their interest is, concern about this leads to interventions such as the feeding of birds and other wildlife on the assumption that they cannot take care of themselves. These worries generate a concern in many to protect wildlife on the unfounded assumption that without human interference, all would disappear.

Stage 3: Demand Action

By this stage wildlife and fishery scientists have begun doing many excellent studies on how some populations of wildlife are in serious trouble. The crux at this point is that often the origin of these problems are human actions in cutting down forests, clearing land for agriculture and housing, and polluting the general environment. The problem is people do things related to “progress” and then find it is killing wildlife. If you need an example, think DDT or seismic lines. The public grows more aware and demands conservation action. These demands are translated into small amounts of government action with large amounts of publicity.

Stage 4: Achieve Action

The consequences of the human exploitation of the earth’s resources begins to bite, largely driven by climate emergencies. Much pressure from NGOs and even business people starts to result in action. Wildlife and fisheries agencies make progress but almost always on the scale of single species management often constrained by state or provincial boundaries. Who is in charge of this mess? Biodiversity becomes the cry of the age, and even the New York Times begins to realize that the Earth consists of more than human beings. But while there is more talk, there is less understanding because of the shouting of people who know very little about these conservation issues and how tangled they are. It is important to appear to be on the side of the angels, so progress is slower than one would like.

Stage 5: Understand the Problem

We have barely entered this stage. To be sure ecologists have been at this Stage for many years with reasonable understanding of how to ameliorate conservation problems, but still too few powers that be are convinced, so that we continue to provide subsidies to oil and gas companies that are busy destroying the earth. Subsidies can go in good or bad directions, but few of us can comprehend the volumes of money being committed to subsidies in all directions. We hear promises to achieve X by 2030, and Y by 2050, and still we believe these when we can just look up and see that few of the promises of the last 30 years have been achieved. Few beyond ecologists understand that it is communities and ecosystems that must be protected but almost all our conservation efforts now operate on single species of ecological beauty. Think rhinos.

One hopes for Stage 6 to come to be, but only a small sign of that progress is so far in sight. If only we could convince everyone that conservation issues ought to be treated with the urgency and the funding that COVID has obtained, we could press ahead with more serious conservation objectives. But it is more than declaring that we should protect 30% of our wild areas. Even if we can achieve the 30% goal in the next 8 years, it is but a start toward understanding the stewardship of the Earth if we do not know how the machinery of nature works. Alas, it is a long road ahead being driven by humans who are short-sighted. Can we avoid Plus ça change?

On Conservation Complexities

It is too often the case that biodiversity problems are managed by single species solutions. If you have too many deer in your parks or conservation areas, start a culling program. If your salmon fishing stocks are declining, cull seals and sea lions. The overall issue confounding these kinds of ‘solutions’ are now being recognized as a failure to appreciate the food web of the community and ecosystem in which the problem is embedded. Much of conservation action is directed at heading back to the “good old days” without very much data about what the ecosystem was like in the “good old days”.

Problems with introduced species top the list of conservation dilemmas, and nowhere are these problems more clearly illustrated than by the conservation dilemmas of New Zealand and Australia. If we concentrate our management efforts on introduced predators or herbivores, we face a large set of conservation issues, well-illustrated by the current New Zealand situation (Leathwick and Byrom 2023, Parkes and Murphy 2003).

New Zealand is a particularly strong case history because we have a good knowledge of its indigenous biodiversity from the time that people colonized these islands, as well as reasonable information about how things have changed since Europeans colonized the country (Thomson 1922). It is in some respects the classic case of biodiversity impacts from introduced species. The introduced species list is large and I can talk only about part of these species introduced mostly in the late 1800s. Seven species of deer were released in New Zealand, along with chamois, hares, rabbits, cats, hedgehogs, three mustelid species, brushtail possums, rats, house mice, along with all the usual farm animals like cattle, horses, and dogs (King & Forsyth 2021). The first concerns began about 100 years ago over ungulate browsing in forests and grasslands. Deer control began about 1930, and over 3 million deer were shot between 1932 and 1954. Caughley (1983) showed that this amount of control did not reduce the impact of browsing and grazing by ungulates in native ecosystems. Control and harvesting efforts decreased in recent years partly from a lack of government funding with the result that deer numbers have rebounded. The recognition of the impact of other pests like rabbits, weasels, and rats led to a focus on poison campaigns. Brushtail possum control with poisons was started to reduce tree browsing damage by the 1970s and gradually increased to reduce TB transmission to domestic livestock by the 1990s. Large scale predator control began in the late 1990s with a focus on rats, stoats (weasels, Mustela erminea), and possums with good success in preventing declines in threatened bird species. All this history is covered in detail in Leathwick and Byrom (2023).

These efforts led to a declaration in 2016 of “Predator Free New Zealand 2050” (PF2050) a compelling promise that would alleviate biodiversity problems by making New Zealand free of possums, mustelids, and rats by 2050, and predator control has thus became the focus of recent conservation action. The 2050 part of the promise was always a worry, since governments in general promise much in advances by that year, but the optimistic view is that predator control will achieve this objective if careful planning is made, adequate funding is available (c.f. Department of Conservation 2021), and well-articulated guidelines for eradication of invasive species are followed (Bomford & O’Brien 1995). The message is that biodiversity goals can be achieved if we move from single species management to a stable system of ecosystem management in the broad sense, including strong research, good public participation and support toward these goals, and that biodiversity conservation will be greatly boosted by thorough consultation with (if not leadership by) the indigenous groups involved.

The New Zealand specific situation cannot be applied directly to all biodiversity concerns, but the New Zealand conservation story and the 12 recommendations given in Leathwick and Byrom (2023) show the necessity of goal definition and coordination between the public, government, and private foundations if we are to maximize the effectiveness of our approach to the biodiversity crisis. Not every conservation issue involves introduced species, but the principle must be: What do we want to achieve, and how are we going to get there?

Bomford, M, & O’Brien, P 1995. Eradication or control for vertebrate pests? Wildlife Society Bulletin 23, 249–255.

Caughley, G. (1983) The Deer Wars: The Story of Deer in New Zealand. Heinemann, Auckland. ISBN: 0868633895.

Department of Conservation (2020). Annual Report. Available at: https://www.doc.govt. nz/nature/pests-and-threats/predator-free-2050/goal-tactics-and-new-technology/tools-to-market/.    See also: PF2050-Limited-Annual-Report-2022.pdf

King, C.M. & Forsyth, D.M. (2021). eds. The Handbook of New Zealand Mammals. 3rd edition. CSIRO Publishing, Canberra. ISBN 978-1988592589.

Leathwick, J.R. & Byrom, A.E. (2023) The rise and rise of predator control: a panacea, or a distraction from conservation goals? New Zealand Journal of Ecology, 47, 3515. doi: 10.20417/nzjecol.47.3515.

Parkes, J. & Murphy, E. (2003) Management of introduced mammals in New Zealand. New Zealand Journal of Zoology, 30, 335-359. doi:10.1080/03014223.2003.9518346.

Thomson, G.M. (1922) The Naturalisation of Animals and Plants in New Zealand. The University Press, Cambridge, England. doi: 10.5962/bhl.title.28093.

Should Empirical Ecology be all Long-term?

The majority of empirical ecology research published in our journals is short-term with the time span dictated by the need for 1–2-year Master’s degree studies and 3-4-year PhD research. This has been an excellent model when there was little of a framework for researching the critical questions ecologists ought to answer. Much of ecology in the good old days was based on equilibrium models of populations, communities, and ecosystems, an assumption we know to be irrelevant to a world with a changing climate. Perhaps we should have listened to the paleoecologists who kept reminding us that there was monumental change going on in the eras of glaciation and much earlier in the time of continental drift (Birks 2019). All of this argues that we need to change direction from short-term studies to long-term studies and long-term thinking.

There are many short-term ecological studies that are useful and should be done. It is necessary for management agencies to know if the spraying of forest insect pests this year reduces damage next year, and many similar problems exist that can be used for student projects. But the big issues of our day are long term problems, defined in the first place by longer than the research lifespan of the average ecologist, about 40 years. These big issues are insufficiently studied for two reasons. First, there is little funding for long term research. We can find a few exemptions to this statement, but they are few and many of them are flawed. Second, we as research scientists want to do something new that no one has done before. This approach leads to individual fame and sometimes fortune and is the social model behind many of the research prizes that we hear about in the media, the Nobel Prize, the MacArthur Awards, the National Medal of Science, the Kyoto Prize and many more. The point here is not that we should stop giving these awards (because they are socially useful), but that we should take a broader perspective on how research really works. Many have recognized that scientific advances are made by groups of scientists standing on the shoulders of an earlier generation. Perhaps some of the awards in medicine recognize this more frequently than other areas of science. My point is that large problems in ecology require a group effort by scientists that is too often unrecognized in favour of the individual fame model of science prizes.

A few examples may exemplify the need in ecology to support group studies of long-term problems. The simplest cases are in the media every day. The overharvesting of trees continues with little research into the long-term recovery of the harvested area and exactly how the forest community changes as it recovers. We mine areas for minerals and drill and mine tar sands for oil and gas with little long-term view of the recovery path which may stretch to hundreds or thousands of years while our current research program is long-term if it goes for 10 years. Canada has enough of these disturbance problems to fill the leger. The Giant Gold Mine in the Northwest Territories of Canada mined 220,000 kg of gold from 1948 to 2004 when it closed. It left 237 tonnes of arsenic trioxide dust, a by-product for extracting gold. The long-term ecosystem problems from this toxic compound will last for centuries but you might expect it will be much sooner forgotten than subjected to long-term study.

So where are we ecologists with respect to these large problems? We bewail biodiversity loss and when you look at the available data and the long-term studies you would expect to measure biodiversity and, if possible, manage this biodiversity loss. But you will find only piecemeal short-term studies of populations, communities, and ecosystems that are affected. We tolerate this unsatisfactory scientific situation even for ecosystems as iconic as the Great Barrier Reef of eastern Australia where we have a small number of scientists monitoring the collapse of the reef from climate change. The only justification we can give is that “Mother Nature will heal itself” or in the scientific lingo, “the organisms involved will adapt to environmental change”. All the earth’s ecosystems have been filtered through a million years of geological change, so we should not worry, and all will be well for the future, or so the story goes.

I think few ecologists would agree with such nonsense as the statements above, but what can we do about it? My main emphasis here is long-term monitoring. No matter what you do, this should be part of your research program. If possible, do not count birds on a plot for 3 years and then stop. Do not live trap mice for one season and think you are done. If you have any control over funding recommendations, think continuity of monitoring. Long-term monitoring is a necessary but not a sufficient condition for managing biodiversity change.

There are many obstacles interfering with achieving this goal. Money is clearly one. If your research council requests innovation in all research proposals, they are probably driven by Apple iPhone producers who want a new model every year. For the past 50 years we have been able to fund monitoring in our Yukon studies without ever using the forbidden word monitor because it was not considered science by the government granting agencies. In one sense it is not whether you consider science = innovation or not, but part of the discussion about long term studies might be shifted to consider the model of weather stations, and to discuss why we continue to report temperatures and CO2 levels daily when we have so much past data. No one would dream of shutting down weather monitoring now after the near fiasco around whether or not to measure CO2 in the atmosphere (Harris, 2010, Marx et al. 2017).

Another obstacle has been the destruction of research sites by human developments. Anyone with a long history of doing field research can tell you of past study areas that have been destroyed by fire or are now parking lots, or roads, or suburbia. This problem could be partly alleviated by the current proposals to maintain 30% of the landscape in protected areas. We should however avoid designating areas like the toxic waste site of the Giant Gold Mine as a “protected area” for ecological research.

Where does this all lead? Consider long-term monitoring if you can do the research as part of your overall program. Read the recent contributions of Hjeljord, and Loe (2022) and Wegge et al. (2022) as indicators of the direction in which we need to move, and if you need more inspiration about monitoring read Lindenmayer (2018).

Birks, H.J.B. (2019) Contributions of Quaternary botany to modern ecology and biogeography. Plant Ecology & Diversity, 12, 189-385.doi: 10.1080/17550874.2019.1646831.

Harris, D.C. (2010) Charles David Keeling and the story of atmospheric CO2 measurements. Analytical Chemistry, 82, 7865-7870.doi: 10.1021/ac1001492.

Hjeljord, O. & Loe, L.E. (2022) The roles of climate and alternative prey in explaining 142 years of declining willow ptarmigan hunting yield. Wildlife Biology, 2022, e01058.doi: 10.1002/wlb3.01058.

Lindenmayer, D. (2018) Why is long-term ecological research and monitoring so hard to do? (And what can be done about it). Australian Zoologist, 39, 576-580.doi: 10.7882/az.2017.018.

Marx, W., Haunschild, R., French, B. & Bornmann, L. (2017) Slow reception and under-citedness in climate change research: A case study of Charles David Keeling, discoverer of the risk of global warming. Scientometrics, 112, 1079-1092.doi: 10.1007/s11192-017-2405-z.

Wegge, P., Moss, R. & Rolstad, J. (2022) Annual variation in breeding success in boreal forest grouse: Four decades of monitoring reveals bottom-up drivers to be more important than predation. Ecology and Evolution.12, e9327. doi: 10.1002/ece3.9327.